DEVELOPMENT... OpenML
Run
51837

Run 51837

Task 1742 (Learning Curve) spambase Uploaded 07-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.MultiBoostAB_REPTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001
weka.MultiBoostAB_REPTree(2)_C3
weka.MultiBoostAB_REPTree(2)_P100
weka.MultiBoostAB_REPTree(2)_S1
weka.MultiBoostAB_REPTree(2)_I10
weka.MultiBoostAB_REPTree(2)_Wweka.classifiers.trees.REPTree

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

21 Evaluation measures

Area under ROC curve
0.9783 ± 0.0081
Per class
Build CPU time
0.3419
Build memory
451497338.1714
F measure
0.946 ± 0.0125
Per class
Kappa
0.8866 ± 0.0262
KB relative information score
0.8841 ± 0.0257
Mean absolute error
0.0545 ± 0.0118
Mean prior absolute error
0.4776 ± 0.0002
Number of instances
4601
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.946 ± 0.0126
Per class
Predictive accuracy
0.9461 ± 0.0125
Prior entropy
0.9674 ± 0.0006
Recall
0.9461 ± 0.0125
Per class
Relative absolute error
0.1141 ± 0.0248
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.223 ± 0.026
Root relative squared error
0.4563 ± 0.0535
SciMark benchmark
1678.1065